Codes on graphs: normal realizations
IEEE Transactions on Information Theory
Extrinsic information transfer functions: model and erasure channel properties
IEEE Transactions on Information Theory
Tight bounds for LDPC and LDGM codes under MAP decoding
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Sharp Bounds on Generalized EXIT Functions
IEEE Transactions on Information Theory
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Consider transmission over a binary additive white gaussian noise channel using a fixed low-density parity check code. We consider the posterior measure over the code bits and the corresponding correlation between two codebits, averaged over the noise realizations. We show that for low enough noise variance this average correlation decays exponentially fast with the graph distance between the code bits. One consequence of this result is that for low enough noise variance the GEXIT functions (further averaged over a standard code ensemble) of the belief propagation and optimal decoders are the same.